attention

Attention warps memory space

screenshot semantic space

A recent study reveals that when we focus on searching for something, regions across the brain are pulled into the search. The study sheds light on how attention works.

In the experiments, brain activity was recorded as participants searched for people or vehicles in movie clips. Computational models showed how each of the roughly 50,000 locations near the cortex responded to each of the 935 categories of objects and actions seen in the movie clips.

Meditating leads to better grades

meditating on a flame

Three classroom experiments have found that students who meditated before a psychology lecture scored better on a quiz that followed than students who did not meditate. Mood, relaxation, and class interest were not affected by the meditation training.

The noteworthy thing is that the meditation was very very basic — six minutes of written meditation exercises.

Why it's hard to stay on task

dilated eye

Why do we find it so hard to stay on task for long? A recent study uses a new technique to show how the task control network and the default mode network interact (and fight each other for control).

In favor of nature’s benefits for cognition

nature scene

As many of you will know, I like nature-improves-mind stories. A new twist comes from a small Scottish study, in which participants were fitted up with a mobile EEG monitor that enabled their brainwaves to be recorded as they walked for 25 minutes through one of three different urban settings: an urban shopping street, a path through green space, or a street in a busy commercial district.

Frequent multitaskers are the worst at it

A survey of college students found that those who scored highest in multitasking ability were also least likely to multitask, while those who scored lowest were most likely to engage in it.

I’ve reported often on the perils of multitasking. Here is yet another one, with an intriguing new finding: it seems that the people who multitask the most are those least capable of doing so!

The study surveyed 310 undergraduate psychology students to find their actual multitasking ability, perceived multitasking ability, cell phone use while driving, use of a wide array of electronic media, and personality traits such as impulsivity and sensation-seeking.

Those who scored in the top quarter on a test of multitasking ability tended not to multitask. Some 70% of participants thought they were above average at multitasking, and perceived multitasking ability (rather than actual) was associated with multitasking. Those with high levels of impulsivity and sensation-seeking were also more likely to multitask (with the exception of using a cellphone while driving, which wasn’t related to impulsivity, though it was related to sensation seeking).

The findings suggest that those who multitask don’t do so because they are good at multitasking, but because they are poor at focusing on one task.

How urban living affects attention

A comparison of traditional African villagers and those who have moved to town indicates that urban living improves working memory capacity even as it makes us more vulnerable to distraction.

Another study looking into the urban-nature effect issue takes a different tack than those I’ve previously reported on, that look at the attention-refreshing benefits of natural environments.

In this study, a rural African people living in a traditional village were compared with those who had moved to town. Participants in the first experiment included 35 adult traditional Himba, 38 adolescent traditional Himba (mean age 12), 56 adult urbanized Himba, and 37 adolescent urbanized Himba. All traditional Himba had had little contact with the Western world and only spoke their native language; all adult urbanized Himba had grown up in traditional villages and only moved to town later in life (average length of time in town was 6 years); all adolescent urbanized Himba had grown up in town the town and usually attended school regularly.

The first experiments assessed the ability to ignore peripheral distracting arrows while focusing on the right or left direction of a central arrow.

There was a significant effect of urbanization, with attention being more focused (less distracted) among the traditional Himba. Traditional Himba were also slower than urbanized Himba — but note that there was substantial overlap in response times between the two groups. There was no significant effect of age (that is, adolescents were faster than adults in their responses, but the effect of the distracters was the same across age groups), or a significant interaction between age and urbanization.

The really noteworthy part of this, was that the urbanization effect on task performance was the same for the adults who had moved to town only a few years earlier as for the adolescents who had grown up and been educated in the town. In other words, this does not appear to be an educational effect.

The second experiment looked at whether traditional Himba would perform more like urbanized Himba if there were other demands on working memory. This was done by requiring them to remember three numbers (the number words in participants’ language are around twice as long as the same numbers in English, hence their digit span is shorter).

While traditional Himba were again more focused than the urbanized in the no-load condition, when there was this extra load on working memory, there was no significant difference between the two groups. Indeed, attention was de-focused in the traditional Himba under high load to the same degree as it was for urbanized Himba under no-load conditions. Note that increasing the cognitive load made no difference for the urbanized group.

There was also a significant (though not dramatic) difference between the traditional and urbanized Himba in terms of performance on the working memory task, with traditional Himba remembering an average of 2.46/3 digits and urbanized Himba 2.64.

Experiment 3 tested the two groups on a working memory task, a standard digit span test (although, of course, in their native language). Random sequences of 2-5 digits were read out, with the participant being required to say them aloud immediately after. Once again, the urbanized Himba performed better than the traditional Himba (4.32 vs 3.05).

In other words, the problem does not seem to be that urbanization depletes working memory, rather, that urbanization encourages disengagement (i.e., we have the capacity, we just don’t use it).

In the fourth experiment, this idea was tested more directly. Rather than the arrows used in the earlier experiments, black and white faces were used, with participants required to determine the color of the central face. Additionally, inverted faces were sometimes used (faces are stimuli we pay a lot of attention to, but inverting them reduces their ‘faceness’, thus making them less interesting).

An additional group of Londoners was also included in this experiment.

While urbanized Himba and Londoners were, again, more de-focused than traditional Himba when the faces were inverted, for the ‘normal’ faces, all three groups were equally focused.

Note that the traditional Himba were not affected by the changes in the faces, being equally focused regardless of the stimulus. It was the urbanized groups that became more alert when the stimuli became more interesting.

Because it may have been a race-discrimination mechanism coming into play, the final experiment returned to the direction judgment, with faces either facing left or right. This time the usual results occurred – the urbanized groups were more de-focused than the traditional group.

In other words, just having faces was not enough; it was indeed the racial discrimination that engaged the urbanized participants (note that both these urban groups come from societies where racial judgments are very salient – multicultural London, and post-apartheid Namibia).

All of this indicates that the attention difficulties that appear so common nowadays are less because our complex environments are ‘sapping’ our attentional capacities, and more because we are in a different attentional ‘mode’. It makes sense that in environments that contain so many more competing stimuli, we should employ a different pattern of engagement, keeping a wider, more spread, awareness on the environment, and only truly focusing when something triggers our interest.

Reference: 

[3273] Linnell, K. J., Caparos S., de Fockert J. W., & Davidoff J. (2013).  Urbanization Decreases Attentional Engagement. Journal of experimental psychology. Human perception and performance.

Daydreaming nurtures creativity?

A small study adds to evidence that time immersed in the natural environment, or perhaps time free of electronic devices, improves creativity. Another suggests it may be the opportunity to daydream that drives this effect.

Back in 2010, I read a charming article in the New York Times about a bunch of neuroscientists bravely disentangling themselves from their technology (email, cellphones, laptops, …) and going into the wilderness (rafting down the San Juan River) in order to get a better understanding of how heavy use of digital technology might change the way we think, and whether we can reverse the problem by immersing ourselves in nature.

Even tiny interruptions can double or treble work errors

A new study quantifies the degree to which tasks that involve actions in a precise sequence are vulnerable to interruptions.

In my book on remembering intentions, I spoke of how quickly and easily your thoughts can be derailed, leading to ‘action slips’ and, in the wrong circumstances, catastrophic mistakes. A new study shows how a 3-second interruption while doing a task doubled the rate of sequence errors, while a 4s one tripled it.

The study involved 300 people, who were asked to perform a series of ordered steps on the computer. The steps had to be performed in a specific sequence, mnemonically encapsulated by UNRAVEL, with each letter identifying the step. The task rules for each step differed, requiring the participant to mentally shift gears each time. Moreover, task elements could have multiple elements — for example, the letter U could signal the step, one of two possible responses for that step, or be a stimulus requiring a specific response when the step was N. Each step required the participant to choose between two possible responses based on one stimulus feature — features included whether it was a letter or a digit, whether it was underlined or italic, whether it was red or yellow, whether the character outside the outline box was above or below. There were also more cognitive features, such as whether the letter was near the beginning of the alphabet or not. The identifying mnemonic for the step was linked to the possible responses (e.g., N step – near or far; U step — underline or italic).

At various points, participants were very briefly interrupted. In the first experiment, they were asked to type four characters (letters or digits); in the second experiment, they were asked to type only two (a very brief interruption indeed!).

All of this was designed to set up a situation emulating “train of thought” operations, where correct performance depends on remembering where you are in the sequence, and on producing a situation where performance would have reasonably high proportion of errors — one of the problems with this type of research has been the use of routine tasks that are generally performed with a high degree of accuracy, thus generating only small amounts of error data for analysis.

In both experiments, interruptions significantly increased the rate of sequence errors on the first trial after the interruption (but not on subsequent ones). Nonsequence errors were not affected. In the first experiment (four-character interruption), the sequence error rate on the first trial after the interruption was 5.8%, compared to 1.8% on subsequent trials. In the second experiment (two-character interruption), it was 4.3%.

The four-character interruptions lasted an average of 4.36s, and the two-character interruptions lasted an average of 2.76s.

Whether the characters being typed were letters or digits made no difference, suggesting that the disruptive effects of interruptions are not overly sensitive to what’s being processed during the interruption (although of course these are not wildly different processes!).

The absence of effect on nonsequence errors shows that interruptions aren’t disrupting global attentional resources, but more specifically the placekeeping task.

As I discussed in my book, the step also made a significant difference — for sequence errors, middle steps showed higher error rates than end steps.

All of this confirms and quantifies how little it takes to derail us, and reminds us that, when engaged in tasks involving the precise sequence of sub-tasks (which so many tasks do), we need to be alert to the dangers of interruptions. This is, of course, particularly true for those working in life-critical areas, such as medicine.

Reference: 

[3207] Altmann, E. M., Gregory J., & Hambrick D. Z. (2013).  Momentary Interruptions Can Derail the Train of Thought. Journal of Experimental Psychology: General. No - Pagination Specified.

Seeing without words

I was listening on my walk today to an interview with Edward Tufte, the celebrated guru of data visualization. He said something I took particular note of, concerning the benefits of concentrating on what you’re seeing, without any other distractions, external or internal. He spoke of his experience of being out walking one day with a friend, in a natural environment, and what it was like to just sit down for some minutes, not talking, in a very quiet place, just looking at the scene.

Simple semantic task reveals early cognitive problems in older adults

A study finds early semantic problems in those with MCI, correlating with a reduced capacity to carry out everyday tasks.

A small study shows how those on the road to Alzheimer’s show early semantic problems long before memory problems arise, and that such problems can affect daily life.

The study compared 25 patients with amnestic MCI, 27 patients with mild-to-moderate Alzheimer's and 70 cognitively fit older adults (aged 55-90), on a non-verbal task involving size differences (for example, “What is bigger: a key or a house?”; “What is bigger: a key or an ant?”). The comparisons were presented in three different ways: as words; as images reflecting real-world differences; as incongruent images (e.g., a big ant and a small house).

Both those with MCI and those with AD were significantly less accurate, and significantly slower, in all three conditions compared to healthy controls, and they had disproportionately more difficulty on those comparisons where the size distance was smaller. But MCI and AD patients experienced their biggest problems when the images were incongruent – the ant bigger than the house. Those with MCI performed at a level between that of healthy controls and those with AD.

This suggests that perceptual information is having undue influence in a judgment task that requires conceptual knowledge.

Because semantic memory is organized according to relatedness, and because this sort of basic information has been acquired a long time ago, this simple test is quite a good way to test semantic knowledge. As previous research has indicated, the problem doesn’t seem to be a memory (retrieval) one, but one reflecting an actual loss or corruption of semantic knowledge. But perhaps, rather than a loss of data, it reflects a failure of selective attention/inhibition — an inability to inhibit immediate perceptual information in favor of more relevant conceptual information.

How much does this matter? Poor performance on the semantic distance task correlated with impaired ability to perform everyday tasks, accounting (together with delayed recall) for some 35% of the variance in scores on this task — while other cognitive abilities such as processing speed, executive function, verbal fluency, naming, did not have a significant effect. Everyday functional capacity was assessed using a short form of the UCSD Skills Performance Assessment scale (a tool generally used to identify everyday problems in patients with schizophrenia), which presents scenarios such as planning a trip to the beach, determining a route, dialing a telephone number, and writing a check.

The finding indicates that semantic memory problems are starting to occur early in the deterioration, and may be affecting general cognitive decline. However, if the problems reflect an access difficulty rather than data loss, it may be possible to strengthen these semantic processing connections through training — and thus improve general cognitive processing (and ability to perform everyday tasks).

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